Two-Way ANOVA
Return to Behavioral Research Methods This is the statistical test used when you have two independent variables with at least two levels (or conditions) each and one dependent variable. The independent variables are ideally nominal but can be ordinal. The dependent variable is ideally ratio but can be interval. : For example, pretend the two independent variables are hair color (blonde, brunette, & red) and gender (male & female). The research question could be, "Do gender and hair color have a relationship with height?" The dependent variable can be height because it is continuous. The simplest form of a Two-Way ANOVA is a 2x2 factorial design. This is when you have 2 independent variables (factors) with 2 levels (conditions) in each. When examining the differences, you look for the Main Effect ''of each factor and the ''Interaction ''between the factors. The Main Effect is differences caused by a single factor. The Interaction is when a combination of the factors caused a difference. Like the One-Way ANOVA, results only indicate if there is a difference. Post Hoc tests must be done to determine the location of the differences. 'Independent Measures' Participants in one pair of conditions cannot be in another pair of conditions. When represented by a table, each cell contains a different group of participants. :: For example, pretend a study was done to compare the test scores between genders (males/females) and treatment conditions (medicine/placebo). Each independent variables have two levels (or conditions). '''Independent Measures in SPSS' #Click on 'Analyze' -> 'General Linear Model' -> 'Univariate' #Move your IVs from the box on the left to the box on the right labeled 'Fixed Factor(s)' #Move your DV from the box on the left to the box on the right labeled 'Dependent Variable' #Click on the 'Options' button on the right #Check the box for 'Descriptive Statistics' #Click 'Continue' #Click 'OK' #Your output should appear 'Repeated Measures' Ideally, the same participants are used in every condition. When represented by a table, each cell contains the same group of participants. :: For example, let's say we want to know if the weather (sunny/rainy) and what a person wears (shorts/pants) affects the time it takes them to drive to work. We can use the same people for all of the levels (or conditions). A Repeated Measures ANOVA can also be used if you used matched groups instead. This means each group of participants is similar one at least one other measure. :: For example, imagine a study was done to compare the effects of eye color (brown/blue) and hair color (brunette/blonde) on GPA. To use matched groups, the researchers made sure to find participants who had taken the same classes and have similar study habits. Repeated Measures in SPSS # Click on 'Analyze' -> 'General Linear Model' -> 'Repeated Measures' # Enter your factor names and define the number of levels for each (click 'Add' after entering this information for each factor) # Click 'Define' # Assign labels to each of your levels for each factor # Determine the numeric combinations of the treatment conditions # Enter the factors in the right order by clicking them from the left box to the right box labeled 'Within-Subjects Variables' # Click on the 'Options' button and check the 'Descriptive Statistics' box # Click 'Continue' # Click 'OK' # Your output should appear